Online advertising may be an important source of revenue for enterprises engaged in electronic commerce. A number of different kinds of web page based online advertisements are currently in use, along with various associated distribution requirements, advertising metrics, and pricing mechanisms. Processes associated with technologies such as Hypertext Markup Language (HTML) and Hypertext Transfer Protocol (HTTP) enable a web page to be configured to contain a location for inclusion of an advertisement. A page may not only be a web page, but any other electronically created page or document. An advertisement can be selected for display each time the page is requested, for example, by a browser or server application.
Online advertising may be linked to online searching. Online searching is a very common way for consumers to locate information, goods, or services on the Internet. A consumer may use an online search engine to type in one or more keywords to search for other pages or web sites with information related to the keyword(s). The advertising that is shown on the search engine page may be related to the keyword(s). In particular, a search results page may be displayed, which may include the search results, as well as advertisements, related to the keyword(s) that produced the search results.
The advertisements related to search results shown as a search engine page, or based on content from other pages may be targeted to the consumer viewing the page. In particular, advertisers would like for their advertisements to be shown to those consumers who would be most likely to select the advertisement and to view the advertiser's page, or purchase the advertiser's goods or services. Accordingly, the advertising provider, such as a search engine, may attempt to determine the intent of consumers when those consumers view or interact with a web page.
Consumers use the Internet and search engines to find information and make decisions among online entities such as websites, online companies, or online services, independent of geographic constraints. For example, online retailers may provide goods or services to any location in the United States. Accordingly, contextual relevancy plays a role in driving economic value by helping consumers make decisions in their online lives. For example, the Internet may be used to help consumers find useful online services, online merchants and online information. In addition, the Internet is evolving into a type of informational utility that helps consumers make important local or geographic-specific decisions in their offline lives as well. Consumers are turning to the Internet for services that help them manage more of their day-to-day offline activities and needs.
A search engine may attempt to determine the intent of a consumer who just performed a search. In one example, the intent that is analyzed may be geographic, such as for a search for the keyword “dry cleaning,” it is likely that the intent of the consumer is a local intent, such that the results should be directed to a specific geographic location. Local intent may refer to whether the consumer would like geographically specific (local) results or whether there is a geographic component to the search query. Accordingly, the search engine may determine the presence of local intent of certain keywords and attempt to provide search results that are targeted to a specific geography. Local intent may refer to any aspect of intent that the consumer would like to see in the results. The search engine determines and analyzes that intent to produce search results that satisfy the intent of the consumer. The local intent may be geo-related, rather than geo-specific, such that search results for goods or services from a national online retailer may be targeted to minimize shipping costs or other expenses.
The consumer who searches for a local dry cleaner should be shown content, advertising and listings that are geographically relevant because it is likely the consumer is only concerned with dry cleaners located at a certain geographic location. In addition, the relevant advertisements may relate to which local dry cleaners have specials, which don't use harmful chemicals, which are open late, and which are rated best by their community. General online information or websites about “dry cleaning” may not be relevant to a consumer concerned only with local dry cleaners. Directory information, social media, maps, and advertising may all contribute to help the consumer make the best decision. Accordingly, geographic relevancy plays a greater role (in combination with contextual relevancy) in driving overall relevancy.
Some consumers may explicitly geo-modify their searches to specify a location. For example, a consumer may search for “Chicago dry cleaning,” which shows local intent for dry cleaners in Chicago. However, there may be hundreds of dry cleaners in Chicago, and the geographic location may need to be narrower than Chicago to achieve useful results. In addition, smaller, lesser-known towns or cities that are included in a search may result in search results that are not relevant to the specific location that is referenced. Further, many users fail to explicitly geo-modify searches, so the search engine must determine whether a consumer would like geo-specific results and how big a range of geography should be covered.
As the amount of local search traffic increases, there is a need for a search engine to respond with more geographically relevant results. Search behavior with local intent may gradually increase over time, as consumers receive more relevant local media and advertising in response to local keyword searches. Search traffic may contain more local intent, as users increasingly rely on the Internet as a primary source of information for their local purchasing decisions. Accordingly, a system that accurately determines when a consumer has local intent and determines the geographical scope of that intent in order to select the most relevant content and/or advertisements would be beneficial.